Introduction to Statistics 1

THIS COURSE IS APPROPRIATE TO TAKE AT ANY POINT IN A STUDENT?S HIGH SCHOOL MATH SEQUENCE AFTER ALGEBRA II.

PREREQUISITE: A MINIMUM OF C- IN ALGEBRA II OR IMP 3 OR CONFERENCE WITH DEPARTMENT HEAD.

Did you ever wonder what you can really know from a set of data or
statistics about, say, racial profiling or global warming? This course
begins with an in-depth study of variability, in particular categorizing
and quantifying different sources of variability in a data set. Topics
include: Measurement variation, natural variation, production variation,
sample variation, data and probability distributions, and measures of
center and dispersion. These concepts are then applied to the analysis
of bivariate data sets: correlation, residuals and least-squares lines,
and linear and non-linear model fitting. Emphasis is placed on assessing
the predictive value of the models. This course challenges students to
analyze real data and confront the assumptions, power and limits of
statistical analysis. The course makes extensive use of Fathom data
analysis software. Students analyze data, prepare reports and make
presentations of their findings throughout the course.